New KPMG research of more than 2,000 global business leaders finds that AI adoption is accelerating fast – but the gap between organisations capturing real value and those still chasing it comes down to two things: who owns AI outcomes, and whether organisations can see where the money is going.
The findings, published in KPMG’s Global AI Pulse: Q2 2026, draw on responses from senior leaders across 20 countries at organisations with annual revenues exceeding $50 million.
The picture that emerges is of an enterprise AI landscape entering a more demanding, more consequential phase – one where experimentation is no longer enough and financial discipline is becoming as important as technical capability.
AI Enters Everyday Work – But ROI Remains Elusive
Perhaps the most telling headline in the report is the surge in what KPMG calls the “driving adoption” stage of AI maturity.
Twenty-two percent of organisations now describe AI as part of everyday work, up sharply from 13 percent in Q1 2026 – the largest single-quarter shift at any stage on the maturity curve.
AI also retained its status as a top investment priority, cited by 79 percent of leaders (up from 74 percent in Q1), with average AI spending holding steady at $188 million.
But momentum and return are not the same thing. Only seven percent of leaders report having established ROI from AI – a figure that looks particularly stark against the 24 percent facing pressure from investors to demonstrate value.
For all the energy going into AI deployment, the majority of organisations are still struggling to close the loop between investment and measurable outcome.
The response from many leaders has been to focus on the human side of the equation.
Progress in human-AI collaboration has jumped to 71 percent, up from 60 percent in Q1, and 48 percent of organisations are actively upskilling their workforce. The logic is straightforward: technology alone does not deliver business value – people using it effectively do.
The Accountability Gap
One of the more striking structural findings in the report is how unclear AI ownership remains across the C-suite. Only 24 percent of leaders say the CEO is ultimately accountable for AI-driven business outcomes. A further 29 percent point to the broader C-suite – a distribution that, in practice, can mean accountability belongs to everyone and no one.
The consequences of that ambiguity show up clearly in the numbers. Organisations where the CEO is explicitly accountable for decisions informed by AI report higher confidence in their AI strategy (60 percent vs. 22 percent), are significantly more likely to realise meaningful business value (57 percent vs. 21 percent), and are nearly four times more likely to report established ROI (14 percent vs. 4 percent).
Steve Chase, KPMG’s Global Head of AI and Digital Innovation, put it directly: “We’re seeing a clear divide between organisations with leadership accountability at the top and those without.
“These companies are seeing materially better results across the board – greater confidence, higher value realisation and established ROI.”
The implication for enterprise leaders is significant. Governance structures that diffuse AI accountability across the C-suite may feel collaborative, but they appear to dilute outcomes. Clarity at the top translates into results at the bottom line.
The Cost Visibility Problem
Alongside accountability, cost visibility is emerging as one of the sharpest differentiators between AI winners and laggards.
As usage-based AI pricing models become more common – and as token economics add new layers of complexity to spending forecasts – many organisations are finding they simply don’t know how their AI budgets are accumulating.
Nearly a quarter of leaders (23 percent) say they are struggling with usage-based costs. Forty-two percent report only partial visibility into AI spending. A third (33 percent) cite limited understanding of AI cost structures – including how token-based pricing works – as a major challenge when deploying AI agents. Almost half (49 percent) say they have already scaled back AI agent deployments because costs outweighed the benefits.
The organisations that have invested in cost governance are pulling ahead. More than half of global leaders report having AI cost monitoring dashboards in place (53 percent), and 54 percent have embedded cost reviews into AI approval processes. The payoff is substantial: leaders with strong cost visibility are five times more likely to report established ROI (15 percent vs. 3 percent).
Rob Fisher, KPMG’s Global Head of Advisory, framed the shift clearly: “AI is now as much a financial management priority as it is a technology one. The real risk isn’t investing in AI but doing so without cost visibility and an understanding of the economics of AI.
“Organisations that have visibility into their costs and maintain strong oversight are the ones translating AI investment into real, measurable value.”
What This Means for Technology Leaders
For communications and technology leaders – including those managing unified communications and collaboration platforms where AI-powered features are becoming standard – the KPMG findings carry a pointed message. The question is no longer whether to adopt AI, but whether the governance infrastructure exists to manage it responsibly and profitably.
Token economics, usage-based pricing, and agent-driven workflows all introduce cost variables that traditional IT budget models weren’t built to handle. Organisations that build the monitoring, accountability structures, and financial discipline to manage those variables now are positioning themselves to compete on AI outcomes – not just AI spend.
The Q2 data suggests the field is beginning to separate. The organisations investing in visibility and accountability today are already five times more likely to show for it. Those still treating AI as a technology project rather than an enterprise financial priority may find the gap increasingly difficult to close.
